Exploring the association between SNPs and facial morphology in a Spanish population

Understanding and predicting human external phenotypes, particularly facial shape, is of great value for individual identification. However, facial morphology is a highly complex trait. Despite its complexity, recent genome wide association studies (GWAS) have shed light on potential SNPs associated with facial features, offering a first glimpse into the likely genetic background of individual appearance. In this paper we have selected a set of 116 candidate SNPs and studied their association with facial phenotypes in a Spanish population of 412 individuals, highlighting a wide spectrum of facial morphologies worthy of investigation. We performed canonical correlation analysis (CCA) between each SNP and the observed spacial variation in facial shape, from its representation by a dense mesh of 7160 quasi-landmarks, revealing significant associations within different facial segments. In particular, ten SNPs are highlighted for their strong association within this Spanish population, some of them uncovering correlations with novel facial regions. These findings underline the importance and usefulness of conducting candidate SNP studies, not only to validate existing associations but also to unveil novel correlations within subpopulations.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-04-22
DOI
https://doi.org/10.1038/s41598-025-98748-9
Citations
1
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
1.82

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the association between SNPs and facial morphology in a Spanish population

Victoria Suárez-Ulloa, Rubén Martos, Miriam Baeta, Marian M. de Pancorbo et al.
1 citations
Scientific Reports
Genetic Associations and Epidemiology
1.82
article

Exploring the association between SNPs and facial morphology in a Spanish population

Victoria Suárez-Ulloa, Rubén Martos, Miriam Baeta, Marian M. de Pancorbo, Íñigo Olalde, Olatz Moreno-López, Begoña Martínez‐Jarreta, Franziska Wilke, Belén Navarro-López, Susana Jiménez, Susan Walsh
article en
1 citations

Abstract

Understanding and predicting human external phenotypes, particularly facial shape, is of great value for individual identification. However, facial morphology is a highly complex trait. Despite its complexity, recent genome wide association studies (GWAS) have shed light on potential SNPs associated with facial features, offering a first glimpse into the likely genetic background of individual appearance. In this paper we have selected a set of 116 candidate SNPs and studied their association with facial phenotypes in a Spanish population of 412 individuals, highlighting a wide spectrum of facial morphologies worthy of investigation. We performed canonical correlation analysis (CCA) between each SNP and the observed spacial variation in facial shape, from its representation by a dense mesh of 7160 quasi-landmarks, revealing significant associations within different facial segments. In particular, ten SNPs are highlighted for their strong association within this Spanish population, some of them uncovering correlations with novel facial regions. These findings underline the importance and usefulness of conducting candidate SNP studies, not only to validate existing associations but also to unveil novel correlations within subpopulations.

Scientific ReportsVol. 15(1)
Ikerbasque (ES), Universitat de Miguel Hernández d'Elx (ES), University of the Basque Country (ES), Universidad de Granada (ES), Universidad de Zaragoza (ES), Biogipuzkoa Health Research Institute (ES), Instituto de Investigación Sanitaria Aragón (ES), Centro de Tecnologías Aeronauticas (Spain) (ES), Indiana University – Purdue University Indianapolis (US)
Eusko Jaurlaritza, Euskal Herriko Unibertsitatea, European Regional Development Fund, Agencia Estatal de Investigación, European Social Fund
Openalex Percentile: Top 17%
Genetic Associations and Epidemiology
1.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.